Project Summary/Abstract Systems biology seeks to understand how healthy biological systems work, and what goes wrong when they stop working properly and become diseased gaining a holistic view of all of the biochemical components and modeling how they change and interact. The biological system can be a cell, tissue, organism, or even community of organisms. Proteins form nearly all of the machinery within a cell and consequently they greatly influence proper biological function and dysfunction that is associated with disease. Thus, by improving proteome analysis we can improve our understanding of proper function and dysfunction of biological systems. The long-term objective of this research project is to provide improved methods for proteome analysis that increase the detail of the proteins that can be analyzed from a biological sample. Namely, the number of proteoforms identified will be greatly improved and surpass the number of proteins identified with peptide fragment ion spectra based methods. To achieve this large improvement in the detection of proteoforms, a novel microfluidic system will be developed that will integrate intact protein and peptide identification strategies in a seamless and highly automated format. The specific aims of the proposed work will include development of a high-efficiency two-dimensional separation and development of a microfluidic system for rapid sample processing. The performance of the device will be determined through the analysis of Acinetobacter baumannii and human jurkat cells, which represent relatively simple and complex proteomes, respectively. In addition to being a relatively simple model, A. baumannii is clinically relevant because it causes infections in humans and is gaining antibiotic resistance at an alarming rate. Human jurkat cells are involved in the human immune response and have been highly studied and characterized. This high degree of jurkat cell characterization will provide an excellent benchmark to compare the performance of the proposed microfluidic proteomic system against other commonly used proteomics approaches.